Human Verbal Memory Encoding Is Hierarchically Distributed in a Continuous Processing Stream.

Processing of memory is supported by coordinated activity in a network of sensory, association, and motor brain regions. It remains a major challenge to determine where memory is encoded for later retrieval. Here, we used direct intracranial brain recordings from epilepsy patients performing free recall tasks to determine the temporal pattern and anatomical distribution of verbal memory encoding across the entire human cortex. High γ frequency activity (65-115 Hz) showed consistent power responses during encoding of subsequently recalled and forgotten words on a subset of electrodes localized in 16 distinct cortical areas activated in the tasks. More of the high γ power during word encoding, and less power before and after the word presentation, was characteristic of successful recall and observed across multiple brain regions. Latencies of the induced power changes and this subsequent memory effect (SME) between the recalled and forgotten words followed an anatomical sequence from visual to prefrontal cortical areas. Finally, the magnitude of the memory effect was unexpectedly found to be the largest in selected brain regions both at the top and at the bottom of the processing stream. These included the language processing areas of the prefrontal cortex and the early visual areas at the junction of the occipital and temporal lobes. Our results provide evidence for distributed encoding of verbal memory organized along a hierarchical posterior-to-anterior processing stream

Bimodal coupling of ripples and slower oscillations during sleep in patients with focal epilepsy.

OBJECTIVE: Differentiating pathologic and physiologic high-frequency oscillations (HFOs) is challenging. In patients with focal epilepsy, HFOs occur during the transitional periods between the up and down state of slow waves. The preferred phase angles of this form of phase-event amplitude coupling are bimodally distributed, and the ripples (80-150 Hz) that occur during the up-down transition more often occur in the seizure-onset zone (SOZ). We investigated if bimodal ripple coupling was also evident for faster sleep oscillations, and could identify the SOZ. METHODS: Using an automated ripple detector, we identified ripple events in 40-60 min intracranial electroencephalography (iEEG) recordings from 23 patients with medically refractory mesial temporal lobe or neocortical epilepsy. The detector quantified epochs of sleep oscillations and computed instantaneous phase. We utilized a ripple phasor transform, ripple-triggered averaging, and circular statistics to investigate phase event-amplitude coupling. RESULTS: We found that at some individual recording sites, ripple event amplitude was coupled with the sleep oscillatory phase and the preferred phase angles exhibited two distinct clusters (p \u3c 0.05). The distribution of the pooled mean preferred phase angle, defined by combining the means from each cluster at each individual recording site, also exhibited two distinct clusters (p \u3c 0.05). Based on the range of preferred phase angles defined by these two clusters, we partitioned each ripple event at each recording site into two groups: depth iEEG peak-trough and trough-peak. The mean ripple rates of the two groups in the SOZ and non-SOZ (NSOZ) were compared. We found that in the frontal (spindle, p = 0.009; theta, p = 0.006, slow, p = 0.004) and parietal lobe (theta, p = 0.007, delta, p = 0.002, slow, p = 0.001) the SOZ incidence rate for the ripples occurring during the trough-peak transition was significantly increased. SIGNIFICANCE: Phase-event amplitude coupling between ripples and sleep oscillations may be useful to distinguish pathologic and physiologic events in patients with frontal and parietal SOZ

Neural Mechanisms of Episodic Memory formation

In order to remember what you had for breakfast today, you must rely on episodic memory, the memory for personal events situated within a spatiotemporal context. In this dissertation, I use electroencephalographic (EEG) recordings to measure the neural correlates of successful episodic memory formation. The recorded EEG signals simultaneously sample local field potentials throughout the brain, and can be analyzed in terms of specific time-varying oscillatory or spectral components of neural activity which are thought to reflect the concerted activity of neuronal populations. I collected EEG recordings while participants engage in free recall, an episodic memory task during which participants must study and then recall a list of items. In the first chapter, I compare the spectral correlates during encoding of items later remembered to those later forgotten using two separate recording modalities, scalp and intracranial EEG. I find that memory formation is characterized by broad low frequency spectral power decreases and high frequency power increases across both datasets, suggesting that scalp EEG can resolve high frequency activity (HFA) and that low frequency decreases in intracranial EEG are unlikely due to pathology. In the next chapter, I connect these HFA increases to memory-specific processes by comparing study items based on how they are re- called, not whether they are recalled. I find increased HFA in left lateral cortex and hippocampus during the encoding of subsequently clustered items, those items recalled consecutively with their study neighbors at test. The precise time course of these results suggests that context updating mechanisms and item-to-context associative mechanisms support successful memory formation. In the third chapter, I measure how the formation of these episodic associations is modulated by pre-existing semantic associations by including a semantic orienting task during the encoding interval. I find that semantic processing interferes with the formation of new, episodic memories. In the final chapter, I show that the memory benefit for emotionally valenced items is better explained by a contextual mechanism than an attentional mechanism. Together, my work supports the theory that contextual encoding associative mechanisms, reflected by HFA increases in the memory network, support memory formation